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Academic Articles & Research Papers
Showing 20 of 441 academic articles
Nadia Mushtaq Gardazi, Ali Yusny Daud, Muhammad Kamran Malik, Amal Abdullah Bukhari et al. • Artificial Intelligence Review
(2025)
BERT (Bidirectional Encoder Representations from Transformers) has revolutionized Natural Language Processing (NLP) by significantly enhancing the capabilities of language models. This review study examines the complex nature of BERT, inclu...
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cc-by-nc-nd
DOI: https://doi.org/10.1007/s10462-025-11162-5
Srikanth Machiraju, Ritesh Modi • Apress eBooks
(2017)
Natural language processing (NLP) is a field of computer science that is a subset of artificial intelligence and that helps computers understand human language as it is written and spoken. Until recently, it was humans who were trying to un...
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DOI: https://doi.org/10.1007/978-1-4842-3312-2_9
Seyedmostafa Sheikhalishahi, Riccardo Miotto, Joel T. Dudley, Alberto Lavelli et al. • JMIR Medical Informatics
(2019)
BACKGROUND: Novel approaches that complement and go beyond evidence-based medicine are required in the domain of chronic diseases, given the growing incidence of such conditions on the worldwide population. A promising avenue is the seconda...
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DOI: https://doi.org/10.2196/12239
PMC: 6528438
Shijie Chen, Yu Zhang, Qiang Yang • ACM Computing Surveys
(2024)
Deep learning approaches have achieved great success in the field of Natural Language Processing (NLP). However, directly training deep neural models often suffer from overfitting and data scarcity problems that are pervasive in NLP tasks. ...
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Open Access
DOI: https://doi.org/10.1145/3663363
Daniel S. Jurafsky, James Martin (2000)
This book takes an empirical approach to language processing, based on applying statistical and other machine-learning algorithms to large corpora.Methodology boxes are included in each chapter. Each chapter is built around one or more work...
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Alexander Clark, Chris Fox, Shalom Lappin • Wiley eBooks
(2010)
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DOI: https://doi.org/10.1002/9781444324044
Julia El Zini, Mariette Awad • ACM Computing Surveys
(2022)
Despite their success, deep networks are used as black-box models with outputs that are not easily explainable during the learning and the prediction phases. This lack of interpretability is significantly limiting the adoption of such model...
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Open Access
DOI: https://doi.org/10.1145/3529755
Dheya Mustafa, Safaa M. Khabour, Mousa Al-kfairy, Ahmed Shatnawi • PeerJ Computer Science
(2025)
Companies that deliver food (food delivery services, or FDS) try to use customer feedback to identify aspects where the customer experience could be improved. Consumer feedback on purchasing and receiving goods via online platforms is a cru...
DOAJ
Open Access (DOAJ)
DOI: 10.7717/peerj-cs.2669
Miao Jiang, Honghui Chen • Applied Sciences
(2025)
Chinese named entity recognition (NER) is a fundamental natural language processing (NLP) task that involves identifying and categorizing entities in text. It plays a crucial role in applications such as information extraction, machine tran...
DOAJ
Open Access (DOAJ)
DOI: 10.3390/app15052521
Mosima A. Masethe, Sunday O. Ojo, Hlaudi D. Masethe • Computers
(2025)
Meaning conflation deficiency (MCD) presents a continual obstacle in natural language processing (NLP), especially for low-resourced and morphologically complex languages, where polysemy and contextual ambiguity diminish model precision in ...
DOAJ
Open Access (DOAJ)
DOI: 10.3390/computers14090402
Arezo Shakeri, Mina Farmanbar • Alzheimer’s & Dementia: Diagnosis, Assessment & Disease Monitoring
(2025)
Abstract INTRODUCTION Alzheimer's disease (AD) prevalence is increasing, with no current cure. Natural language processing (NLP) offers the potential for non‐invasive diagnostics, social burden assessment, and research advancements in AD. M...
DOAJ
Open Access (DOAJ)
DOI: 10.1002/dad2.70082
Vandeventer Faltin, Anne • Linguistik Online
(2003)
This paper illustrates the usefulness of natural language processing (NLP) tools for computer assisted language learning (CALL) through the presentation of three NLP tools integrated within a CALL software for French. These tools are (i) a ...
DOAJ
Open Access (DOAJ)
Aysenur Arpaci, Asel Usdat Ozturk, Ismail Okur, Sanaz Sadry • BMC Oral Health
(2025)
Abstract Background The field of artificial intelligence (AI) has experienced considerable growth in recent years, with the advent of technologies that are transforming a range of industries, including healthcare and dentistry. Large langua...
DOAJ
Open Access (DOAJ)
DOI: 10.1186/s12903-025-06624-9
Raymond J. Mooney (2005)
In 2005, the Human Language Technology Conference (HLT) and the Conference on Empirical Methods in Natural Language Processing (EMNLP) were held together as a joint conference for the first time. The conference was co-sponsored by the organ...
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Rajendra A. Akerkar • SpringerBriefs in business
(2018)
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DOI: https://doi.org/10.1007/978-3-319-97436-1_5
Pilar López Úbeda, Teodoro Martín‐Noguerol, José Aneiros‐Fernández, Antonio Luna • American Journal Of Pathology
(2022)
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Open Access
DOI: https://doi.org/10.1016/j.ajpath.2022.07.012
Mark Neumann, Daniel King, Iz Beltagy, Waleed Ammar • BioNLP Workshop and Shared Task (BioNLP)
(2019)
Despite recent advances in natural language processing, many statistical models for processing text perform extremely poorly under domain shift. Processing biomedical and clinical text is a critically important application area of natural l...
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DOI: https://doi.org/10.18653/v1/w19-5034
裕二 池谷, Robert Tinn, Hao Cheng, MICHAEL A. LUCAS et al. • ACM Transactions on Computing for Healthcare
(2021)
Pretraining large neural language models, such as BERT, has led to impressive gains on many natural language processing (NLP) tasks. However, most pretraining efforts focus on general domain corpora, such as newswire and Web. A prevailing a...
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Open Access
DOI: https://doi.org/10.1145/3458754
V. Daniel Hunt • Springer eBooks
(1985)
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DOI: https://doi.org/10.1007/978-1-4613-2533-8_7
Karen Spärck Jones • Springer eBooks
(1994)
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DOI: https://doi.org/10.1007/978-0-585-35958-8_1